Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
A Survey on Out-of-Distribution Evaluation of Neural NLP Models
As of 21 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2306.15261.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-21T06:32:19.484+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-12T05:05:08.180946Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-19T17:57:42.537456Z
Reference resolution
0 of 0 outbound references displayed
- verified exact0
- verified fuzzy0
- unresolved0
- parse uncertain0
- malformed identifier0
- metadata mismatch0
External citation measurements
No source-named external measurement is stored.
Outbound references
No outbound reference observations are available for this paper version.
Pith citing papers
Observation 9c9f490c-ead7-4893-92b7-42de94237ae3 · inbound
SelfPrompt: Autonomously Evaluating LLM Robustness via Domain-Constrained Knowledge Guidelines and Refined Adversarial Prompts cites this paper.
SelfPrompt: Autonomously Evaluating LLM Robustness via Domain-Constrained Knowledge Guidelines and Refined Adversarial Prompts A Survey on Out-of-Distribution Evaluation of Neural NLP Models
Reference 2023
- Resolution
- unresolved
- no resolver link, observed 2026-08-12T05:05:08.180946Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation bf0e9f81-fb65-4ea5-a49e-78c95e3c145b · inbound
Quantization Undoes Alignment: Bias Emergence in Compressed LLMs Across Models and Precision Levels cites this paper.
Quantization Undoes Alignment: Bias Emergence in Compressed LLMs Across Models and Precision Levels A Survey on Out-of-Distribution Evaluation of Neural NLP Models
Reference 10
- Resolution
- verified exact
- arxiv_id, observed 2026-05-19T17:57:42.539865Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.